This invention, which is a result of a contract with the United States Department of Energy, relates generally to the art of noise signature analysis and, more specifically, to diagnosing electric motor-operated devices based on motor current noise signature analysis.
In the operation of nuclear power plants and chemical process systems, for example, motor-operated valves (MOVs) are used extensively in various control arrangements. To ensure safe and efficient operation and maintain operational readiness in emergency situations, these valves must be maintained so that they perform properly under all anticipated conditions.
The valves are complex mechanical devices which require periodic careful adjustments or repair to maintain operational readiness. Present methods for diagnosing abnormalities specified by the ASME code, for example, have not proved to be adequate in determining time-dependent degradation (aging), incorrect adjustments, and service wear which may cause failures in emergency situations.
Various methods have been applied in the past to motor-operated devices which include different signature analysis methods, such as vibration signature analysis, direct measured mechanical load-time traces and the like. One example of a load-time trace type signature analysis method is disclosed in U.S. Pat. No. 4,542,649, issued September 24, 1985, for "Motor Operated Valve Analysis Testing System," by Arthur G. Charbonneau et al. In this method, which is specific to the testing of certain MOVs, various pieces of hardware are connected to the valve actuator to obtain information on valve performance. This requires access to the valve to perform the testing and limits testing to specific intervals due to the fact that instrumentation must be attached to the valve during testing and then removed. In this method, a displacement measuring device is used to record the axial motion of the valve operator drive worm which in turn drives a worm gear coupled to the valve stem to open or close the valve. Varying stem loads during operation causes limited axial translation of the drive worm which is spring biased. The resultant measurement is a valve stem load-time trace which is calibrated by means of a load cell arrangement which is also connected to the valve stem during initial testing to calibrate movement of the worm drive relative to the imposed stem load.
In the use of vibration signature analysis, special purpose sensors, usually accelerometers, are mounted on the equipment being monitored, which also requires access to the equipment to mount the sensors during testing. The location and orientation of the accelerometers are critical to the characteristics of the signal obtained. A vibration generated in one part of the mechanical device is altered as it is transmitted through the solids (usually metallic) separating the source from the accelerometer. Thus, the interpretation of a vibration signal is complicated by requiring a knowledge of the vibration transmission characteristics of the equipment. In addition, the analysis of the vibration signals taken at different times (in order to detect changes) is dependent on the ability to reproduce the precise location and direction of mounting of the accelerometers. Thus, in most cases, accelerometers and/or their mounting fixtures are permanently installed on the equipment to be monitored.
Since accelerometers sense vibration primarily in one direction, multiple sensors are necessary to detect the vibrations generated in physically isolated parts of some equipment. Thus, in order to sense all significant vibration directions, it is necessary to install multiple sensors. The results obtained must then be combined to develop the diagnostic information.
In addition, accelerometers will sense sources of vibration which are not generated by the drive motor or the device being driven by the motor which is being evaluated. Not only will these vibration sources affect accuracy and precision, they are in general not an influence on the condition of the equipment, and thus represent extraneous and unnecessary information which must be dealt with.
Accelerometers themselves are subject to degradation if exposed to harsh environments, such as in the containment of nuclear power plants. Their accuracy or precision can be influenced by environmental conditions such as temperature, humidity, nuclear radiation, acoustic noise, corrosive substances, electromagnetic interference, and the like. Although in some cases the effects of one or more of these factors can be removed or compensated for, they represent a significant potential source of error, especially in nuclear plant containment environments.
Therefore, it will be obvious from the above discussion that present signature analysis methods are limited and require additional hardware to be attached to the device during testing. These methods are especially limited when used in diagnosing electric motor-operated devices, such as motor-operated valves and the like in hostile environments. The tests are limited to times when the plants in which the devices are used, such as MOVs in nuclear plants, are shut down for routine maintenance. As a result, most of the information provided by testing under these conditions does not address device operational readiness directly, but rather certain abnormalities that could potentially lead to loss of operational readiness.
In order to provide diagnostic information about operational readiness of an electric motor-driven device, especially those types which are unaccessible during normal operation, the magnitudes and types of abnormalities and their rates of change (trends) with time need to be determined. This allows a judgment to be made as to when corrective action should be taken to prevent loss of operational readiness. In order to obtain this type of diagnostic information, signatures need to be obtained continuously or at least during scheduled periods of normal operation of the device for comparison with previous signatures to not only obtain the current status of the magnitude of abnormalities, but also provide trending information.
Thus, it will be seen that there is a need for a signature analysis method for remotely monitoring the operating characteristics of an electric motor-operated device which does not require access to the device or additional hardware to be attached to the device during monitoring.